Predictive Maintenance

Predictive Maintenance listens continuously to the vibration, temperature, and current signals every rotating and electrical asset produces, and learns what normal looks like for each one. When a bearing starts to wear, a motor begins to overheat, or a current draw drifts out of pattern, the model recognizes the early signature weeks before a human would, long before it shows up as a failure.

Each flagged asset comes with a health score, a trend showing how it's degrading, an estimated time-to-failure window, and a maintenance planning recommendation, so maintenance teams can schedule the repair on their terms instead of reacting to a breakdown. The result is fewer emergency work orders, fewer secondary failures caused by a part running until it fails, and a maintenance budget spent on planned work instead of firefighting.